At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data and Machine Learning are at the heart of Lyft’s products and decision-making. As a member of the Data Science and Machine Learning (ML) team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation. Machine learning interns build systems that make our products predictive, personalized, and adaptive. We’re looking for passionate, driven ML software engineers to take on some of the most interesting and impactful problems in ridesharing.

As an ML SWE intern you will be developing and launching the algorithms that power the platform’s core services. Compared to similarly-sized technology companies, the set of problems that we tackle is incredibly diverse. They cut across transportation, economics, forecasting, mapping, personalization, and adaptive control. 

If you are a student with experience in machine learning workflows, passionate about solving challenging problems using data and working in a dynamic, creative, and collaborative environment, this opportunity is for you.

Responsibilities:

  • Partner with Engineers, Data Scientists, Product Managers, and Business Partners to apply machine learning for business and user impact
  • Design, build, train and test ML models
  • Write production-level code to convert your ML models into working pipelines and launch ML models at scale
  • Perform data analysis and build proof-of-concept to explore and propose ML solutions to both new and existing problems
  • Analyze experimental and observational data, communicate findings, and promote launch decisions
  • Participate in code reviews to ensure code quality and distribute knowledge
  • Develop statistical, machine learning, or optimization models

Experience:

  • Currently pursuing a Bachelor's, Master's, or PhD degree in Computer Science or a related engineering/quantitative field
  • Graduating between December 2022 and June 2023
  • Proficiency in advanced coding principles & machine learning fundamentals, including machine learning models, statistical inference, and classes of ML models 
  • Practical knowledge of how to build efficient end-to-end ML workflows
  • Knowledge of ML libraries like scikit-learn, Tensorflow, PyTorch, Keras, MXNet, etc
  • “Engineer at heart” with a high degree of comfort producing high-quality code
  • Demonstrated oral and written interpersonal skills 
  • Bonus points: Proven ability to effectively turn research ML papers into working code
  • Bonus points: Experience in designing software and ML systems 

Benefits:

  • Great medical, dental, and vision insurance options
  • In addition to holidays, interns receive 1 day paid time off and 3 days sick time off
  • 401(k) plan to help save for your future
  • Pre-tax commuter benefits
  • Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment  without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law. 

Until further notice, Lyft employees working in the United States in any capacity (on a daily or hybrid schedule or as a visitor) are required to provide proof of full vaccination against COVID-19. Employees are considered fully vaccinated two weeks after completion of the entire recommended series of vaccination (usually one or two doses) with a vaccine authorized to prevent COVID-19 by the federal Food and Drug Administration (FDA), including by way of an emergency use authorization. Lyft will maintain records associated with your vaccination history in a way that is compliant with all relevant Federal, state and local laws. Exceptions to this requirement are employees who require religious or medical exemption as approved through Lyft's accommodations process.

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